Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

Growth rates

Heat maps

  • The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
  • The first plot compares growth rate for total cases; the second, growth rate for total deaths.
  • The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
  • The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
    • You can use the plots to track each geography over time and to compare the geographies to one another.
    • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

  • This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
    • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
    • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

  • This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
    • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
    • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

  • This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
  • For each metric, in addition to the tables, the trends for the top states are plotted over time.
    • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)
Ranking State Cases Per Million
1 North Dakota 126,488
2 South Dakota 120,272
3 Utah 103,079
4 Rhode Island 102,690
5 Tennessee 100,310
6 Wisconsin 98,874
7 Iowa 98,394
8 Arizona 96,617
9 Nebraska 95,977
10 Arkansas 92,524
11 Oklahoma 91,748
12 Kansas 91,497
13 Indiana 89,866
14 Idaho 88,636
15 Alabama 88,215
16 Wyoming 87,124
17 Mississippi 87,064
18 Nevada 86,572
19 Illinois 85,939
20 Montana 84,902
21 Louisiana 81,379
22 Minnesota 79,939
23 New Mexico 79,559
24 California 78,854
25 South Carolina 78,561
26 Missouri 77,599
27 Georgia 77,279
28 Kentucky 76,402
29 Texas 76,217
30 Florida 75,141
31 Delaware 74,476
32 New Jersey 72,750
33 Ohio 72,691
34 Alaska 71,467
35 Massachusetts 70,537
36 North Carolina 66,678
37 New York 66,516
38 Colorado 66,493
39 Connecticut 66,136
40 West Virginia 62,839
41 Pennsylvania 62,070
42 Michigan 59,198
43 Maryland 55,365
44 Virginia 53,846
45 District of Columbia 49,042
46 New Hampshire 44,343
47 Washington 39,451
48 Puerto Rico 38,307
49 Oregon 32,238
50 Maine 26,512
51 Hawaii 17,418
52 Vermont 16,955

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)
Ranking State New Cases Per Million
1 Rhode Island 1,366
2 Arizona 1,097
3 South Carolina 843
4 Texas 821
5 Arkansas 768
6 Georgia 759
7 North Carolina 731
8 California 706
9 Kentucky 698
10 New York 646
11 Massachusetts 616
12 Louisiana 599
13 New Hampshire 595
14 Mississippi 580
15 Alabama 578
16 Utah 577
17 New Jersey 567
18 Nebraska 562
19 Delaware 552
20 Florida 537
21 Ohio 531
22 Connecticut 530
23 Oklahoma 524
24 West Virginia 522
25 Idaho 514
26 Virginia 509
27 Tennessee 494
28 Pennsylvania 472
29 Kansas 462
30 Iowa 460
31 Indiana 457
32 Maine 436
33 Wyoming 412
34 Nevada 408
35 New Mexico 406
36 Illinois 375
37 Missouri 375
38 Wisconsin 363
39 Montana 361
40 Maryland 347
41 Washington 292
42 South Dakota 279
43 District of Columbia 273
44 Colorado 266
45 Michigan 245
46 Alaska 226
47 Minnesota 201
48 Vermont 192
49 North Dakota 190
50 Oregon 167
51 Puerto Rico 82
52 Hawaii 56

Total deaths

Table of total deaths per million residents (all 50 states)
Ranking State Deaths Per Million
1 New Jersey 2,337
2 New York 2,125
3 Massachusetts 2,017
4 Rhode Island 1,959
5 Mississippi 1,904
6 Connecticut 1,899
7 South Dakota 1,891
8 North Dakota 1,865
9 Louisiana 1,815
10 Arizona 1,622
11 Illinois 1,611
12 Pennsylvania 1,572
13 Michigan 1,494
14 Arkansas 1,489
15 New Mexico 1,452
16 Indiana 1,424
17 Iowa 1,408
18 Alabama 1,300
19 Nevada 1,271
20 Tennessee 1,260
21 South Carolina 1,237
22 Kansas 1,227
23 District of Columbia 1,224
24 Georgia 1,175
25 Texas 1,175
26 Florida 1,151
27 Missouri 1,125
28 Maryland 1,114
29 Minnesota 1,077
30 Delaware 1,054
31 Wisconsin 1,046
32 Montana 1,031
33 West Virginia 1,031
34 Nebraska 1,001
35 Colorado 959
36 Wyoming 950
37 Idaho 927
38 California 903
39 Ohio 899
40 Kentucky 802
41 North Carolina 800
42 Oklahoma 793
43 New Hampshire 707
44 Virginia 695
45 Puerto Rico 542
46 Washington 542
47 Utah 482
48 Oregon 438
49 Maine 398
50 Alaska 334
51 Vermont 269
52 Hawaii 229

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)
Ranking State New Deaths Per Million
1 Arizona 25
2 Rhode Island 22
3 Pennsylvania 19
4 Alabama 17
5 Arkansas 16
6 California 16
7 Georgia 16
8 Mississippi 16
9 Wyoming 16
10 Nevada 14
11 Louisiana 13
12 Missouri 13
13 New Mexico 13
14 Texas 13
15 Indiana 12
16 Iowa 12
17 Oklahoma 12
18 Tennessee 12
19 West Virginia 12
20 Alaska 11
21 New Jersey 11
22 New York 10
23 Connecticut 9
24 Idaho 9
25 Kentucky 9
26 Massachusetts 9
27 Wisconsin 9
28 Michigan 8
29 North Carolina 8
30 South Carolina 8
31 Florida 7
32 Illinois 7
33 Maryland 7
34 Nebraska 7
35 New Hampshire 7
36 Virginia 7
37 North Dakota 6
38 Ohio 6
39 Washington 6
40 Kansas 5
41 Maine 5
42 Minnesota 4
43 Utah 4
44 Colorado 3
45 Delaware 3
46 District of Columbia 3
47 Oregon 3
48 Puerto Rico 3
49 Montana 2
50 South Dakota 2
51 Vermont 2
52 Hawaii 1

Counties

  • This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
    • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
  • In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Cases Per Million Raw Ranking Percentile
Crowley Colorado 287,576 1 99
Dewey South Dakota 232,858 2 99
Bent Colorado 229,335 3 99
Lincoln Arkansas 228,578 4 99
Lake Tennessee 224,487 5 99
Davidson Tennessee 116,894 254 91
Richland South Carolina 78,851 1499 52
Orange California 72,608 1798 42
York South Carolina 72,212 1816 42
Pierce Washington 36,541 2885 8

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Deaths Per Million Raw Ranking Percentile
Gove Kansas 8,346 1 99
Jerauld South Dakota 7,948 2 99
Dickey North Dakota 6,568 3 99
Grant Nebraska 6,421 4 99
Iron Wisconsin 6,330 5 99
Davidson Tennessee 978 1900 39
Richland South Carolina 936 1956 37
Orange California 802 2168 30
York South Carolina 733 2260 28
Pierce Washington 482 2629 16

Our county percentiles over time

Raw counts

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons